7 citations · 7 across the 4 of their papers we have counts for
4 papers
SUN: Shared Use of Next-token Prediction for Efficient Multi-LLM Disaggregated Serving
Sunghyeon Woo, Ahreum Seo, Jaegwang Lee +6
In multi-model LLM serving, decode execution remains inefficient due to model-specific resource partitioning: since cross-model batching is not possible, memory-bound decoding ofte…
ICaRus: Identical Cache Reuse for Efficient Multi Model Inference
Sunghyeon Woo, Jaeeun Kil, Hoseung Kim +9
Multi model inference has recently emerged as a prominent paradigm, particularly in the development of agentic AI systems. However, in such scenarios, each model must maintain its…
Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback
Kyuyoung Kim, Ah Jeong Seo, Hao Liu +2
Large language models (LLMs) fine-tuned with alignment techniques, such as reinforcement learning from human feedback, have been instrumental in developing some of the most capable…
HyperCLOVA X Technical Report
Kang Min Yoo, Jaegeun Han, Sookyo In +393
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…